Thermal Performance Verification of Thermal Vertical Support Members for the Trans-Alaska Pipeline

1979 ◽  
Vol 101 (4) ◽  
pp. 225-231 ◽  
Author(s):  
S. W. Pearson
Keyword(s):  
Soil Temperature ◽  
Field Test ◽  
Thermal Performance ◽  
Temperature Data ◽  
Temperature Measurements ◽  
Performance Verification ◽  
Vertical Support

Extensive soil temperature measurements have been taken for more than two years in a field test designed to monitor the performance of thermal vertical support members used to support elevated sections of the trans-Alaska pipeline as it crosses marginal permafrost. Thermal aspects of the design are summarized and soil temperature data are presented which demonstrate the ability of the overall thermal vertical support member system to protect the surrounding permafrost.

Time-to-Market: A Practical CFD Application in the Telecom Industry

2003 ◽  
Author(s):  
Edward R. Champion
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Thermal Performance ◽  
Cable Modem ◽  
Time To Market ◽  
Direct Production ◽  
Performance Verification ◽  
Telecom Industry

This paper summarizes the practical use of CFD (Computational Fluid Dynamics) using a commercially available package, FLOTHERM [1], in a tight and highly competitive marketplace to produce a functional pre-production piece of telecom gear with no prototyping for thermal issues. The paper highlights the direct production, noprototype, analytical thermal performance verification of a small CMTS (Cable Modem Termination System) used in telecom applications.

Permafrost Drilling and Soil-Temperature Measurements at Resolute, Cornwallis Island, Canada

Nature ◽  
1952 ◽  
Vol 170 (4330) ◽  
pp. 705-706 ◽  
Author(s):  
ANDREW THOMSON ◽  
P. C. BREMNER
Keyword(s):  
Soil Temperature ◽  
Temperature Measurements ◽  
Cornwallis Island

An Alternative Field Test for Spot Air Conditioning Units

2007 ◽  
Author(s):  
Kau-Fui V. Wong ◽  
Diego Valde´s ◽  
Joshua Goad ◽  
Jesse Losada
Keyword(s):  
Field Test ◽  
Air Conditioning ◽  
Control Volume ◽  
Temperature Measurements ◽  
Coefficient Of Performance ◽  
Data Logging ◽  
Climate Control ◽  
Flow Meter ◽  
Testing Method ◽  
Alternative Field

U.S. governmental standards require that newly produced air conditioners have a SEER (seasonal energy efficiency ratio) rating of over 13, Federal Register (2001), [1]. This rating is closely tied to the COP (coefficient of performance). In fact, the SEER is 3.792 times the COP. Since COP varies with temperature loads, a standard testing method requires the unit to be tested at standard conditions of temperature and humidity. This requires the use of expensive climate control chambers, where the system can be loaded to the specified temperatures. The scope of this paper proposes a simpler, less expensive method to test spot AC (air conditioning) units, as an alternative field test to ASHRAE (American Society of Heating, Refrigeration, and Air-Conditioning Engineers) Standard 128 (2001), [2]. By taking temperature measurements of the appropriate control volume, the COP can be calculated. To obtain steady state, the control volume will be treated as very large (or infinite), placing the unit to be tested outdoors or in a room big enough so that delta T will remain constant. Themocouples in conjunction with data logging software are used to take the temperature measurements, and the mass flow rate is measured by assuming uniform flow and placing a flow meter in the center of the air exhaust, on the evaporator side. The entire system can be assembled into a portable unit composed of a computer, thermocouples, flow meter and a digital multimeter, alternatively, a handheld relative humidity and temperature sensor can be used, ASHRAE (2003), [3]. This would allow not only testing of units before they go into production, but having technicians in the field test the efficiency of units already in operation. The need may be there since there could be a significant drop in the SEER between factory conditions and installed unit, due to variations in duct sizes, losses due to non-ideal installations. Owing to the fact that the COP varies with loading, and our testing method requires no artificial control over loading temperatures, the current study is being conducted to find if the AC unit can perform up to its rating. The second law COP at environmental loading conditions is also evaluated for each of the five AC units tested. The calculated COPII (based on exergy) of the AC units tested do not vary as much (percentage-wise) as the rated COP. Their relative detrimental effects to the environment are probably not that much different from each other.

scholarly journals Analysis of Copernicus’ ERA5 Climate Reanalysis Data as a Replacement for Weather Station Temperature Measurements in Machine Learning Models for Olive Phenology Phase Prediction

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6381
Author(s):  
Noelia Oses ◽  
Izar Azpiroz ◽  
Susanna Marchi ◽  
Diego Guidotti ◽  
Marco Quartulli ◽  
...  
Keyword(s):  
Machine Learning ◽  
Olive Tree ◽  
Reanalysis Data ◽  
Temperature Data ◽  
Temperature Measurements ◽  
Weather Station ◽  
Learning Models ◽  
Phenological Model ◽  
Machine Learning Models ◽  
Phenological Phases

Knowledge of phenological events and their variability can help to determine final yield, plan management approach, tackle climate change, and model crop development. THe timing of phenological stages and phases is known to be highly correlated with temperature which is therefore an essential component for building phenological models. Satellite data and, particularly, Copernicus’ ERA5 climate reanalysis data are easily available. Weather stations, on the other hand, provide scattered temperature data, with fragmentary spatial coverage and accessibility, as such being scarcely efficacious as unique source of information for the implementation of predictive models. However, as ERA5 reanalysis data are not real temperature measurements but reanalysis products, it is necessary to verify whether these data can be used as a replacement for weather station temperature measurements. The aims of this study were: (i) to assess the validity of ERA5 data as a substitute for weather station temperature measurements, (ii) to test different machine learning models for the prediction of phenological phases while using different sets of features, and (iii) to optimize the base temperature of olive tree phenological model. The predictive capability of machine learning models and the performance of different feature subsets were assessed when comparing the recorded temperature data, ERA5 data, and a simple growing degree day phenological model as benchmark. Data on olive tree phenology observation, which were collected in Tuscany for three years, provided the phenological phases to be used as target variables. The results show that ERA5 climate reanalysis data can be used for modelling phenological phases and that these models provide better predictions in comparison with the models trained with weather station temperature measurements.

Modeling Reservoir Temperature Transients and Reservoir-Parameter Estimation Constrained to the Model

2010 ◽  
Vol 13 (06) ◽  
pp. 873-883 ◽  
Author(s):  
Obinna O. Duru ◽  
Roland N. Horne
Keyword(s):  
Flow Rate ◽  
Oil And Gas ◽  
Mechanistic Model ◽  
Operator Splitting ◽  
Temperature Data ◽  
Temperature Measurements ◽  
Solution Technique ◽  
Measured Temperature ◽  
Reservoir Temperature ◽  
Temperature Transient

Summary Permanent downhole gauges (PDGs) provide a continuous source of downhole pressure, temperature, and sometimes flow-rate data. Until recently, the measured temperature data have been largely ignored, although a close observation of the temperature measurements reveals a response to changes in flow rate and pressure. This suggests that the temperature measurements may be a useful source of reservoir information. In this study, reservoir temperature-transient models were developed for single- and multiphase-fluid flows, as functions of formation parameters, fluid properties, and changes in flow rate and pressure. The pressure fields in oil- and gas-bearing formations are usually transient, and this gives rise to pressure/temperature effects appearing as temperature change. The magnitudes of these effects depend on the properties of the formation, flow geometry, time, and other factors and result in a reservoir temperature distribution that is changing in both space and time. In this study, these thermometric effects were modeled as convective, conductive, and transient phenomena with consideration for time and space dependencies. This mechanistic model included the Joule-Thomson effects resulting from fluid compressibility and viscous dissipation in the reservoir during fluid flow. Because of the nature of the models, the semianalytical solution technique known as operator splitting was used to solve them, and the solutions were compared to synthetic and real temperature data. In addition, by matching the models to different temperature-transient histories obtained from PDGs, reservoir parameters such as average porosity, near-well permeabilities, saturation, and some thermal properties of the fluid and formation could be estimated. A key target of this work was to show that temperature measurements, often ignored, can be used to estimate reservoir parameters, as a complement to other more-conventional techniques.

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